Illicit financial flows constitute a global phenomenon of massive but uncertain scale, which erodes government revenues and drives corruption in countries rich and poor. In 2015, the countries of the world committed to a target to reduce illicit flows, as part of the UN Sustainable Development Goals. But five years later, there is still no agreement on how that target should be monitored—to say nothing of how it will be achieved. The term ‘illicit financial flows’ covers a range of corrupt practices, aimed at obtaining immunity or impunity from criminal law, from market regulation and from taxation. Illicit flows occur through many different channels, whether they involve laundering the proceeds of crime, for example, or shifting the profits of multinational companies. There are two consistent features. First, illicit flows are deliberately hidden. These cross-border movements of assets and income streams depend on a set of common tools including opaque company accounts, legal vehicles for anonymous ownership, and the secrecy jurisdictions that provide these services. Second, the overall effect of illicit flows is to reduce the revenue available to states, and to weaken the quality of governance—so there is less money to support human development, and it is less likely to be spent well. In this book, two of the economists most closely involved in the process to develop UN indicators of illicit financial flows offer a critical survey of the existing data and methodologies, identifying the most promising avenues for future improvement and setting out their own proposals.
Author(s): Alex Cobham, Petr Janský
Edition: 1
Publisher: Oxford University Press
Year: 2020
Language: English
Pages: 209
City: Oxford
Tags: Illicit financial flows; Methodologies; Illicit finance; Finance; SDGs; Tax evasion; Tax avoidance; Offshore; Trade mis-invoicing; Profit shifting; Estimates; Data;
Cover
Estimating illicit financial flows: A critical guide to the data, methodologies and findings
Copyright
Dedication
Preface
Contents
List of Figures
List of Tables
Introduction
PART 1: ILLICIT FINANCIAL FLOWS
1: History and overview of ‘IFF’
1.1. Context and Motivation
1.2. Definitions
1.3. Impact
PART 2: ESTIMATES OF IFF SCALE
2: Trade Estimates
2.1. Country-level Trade Estimates: Mirror trade statistics
2.1.1. Overview
2.1.2. Data
2.1.3. Methodology
2.1.4. Results
2.1.5. Conclusions
2.2. Commodity-level Trade Estimates: Abnormal prices
2.2.1. Overview
2.2.2. Data
2.2.3. Methodology
2.2.4. Results
2.2.5. Conclusions
2.3. Transaction-level Trade Estimates: Research frontier
2.3.1. Overview
2.3.2. Data
2.3.3. Methodology
2.3.4. Results
2.3.5. Conclusions
2.4. Conclusions on Trade Estimates
3: Capital and Wealth Estimates
3.1. Capital Flight: Ndikumana and Boyce
3.1.1. Overview
3.1.2. Data
3.1.3. Methodology
3.1.4. Results
3.1.5. Conclusions
3.2. Capital Account Anomalies: Global Financial Integrity (GFI)
3.2.1. Overview
3.2.2. Data
3.2.3. Methodology
3.2.4. Results
3.2.5. Conclusions
3.3. Offshore Capital and Wealth: Henry’s Estimates
3.3.1. Overview
3.3.2. Data
3.3.3. Methodology
3.3.4. Results
3.3.5. Conclusions
3.4. Wealth in Tax Havens: Zucman’s, and Alstadsaeter, Johannesen, & Zucman’s Estimates
3.4.1. Overview
3.4.2. Data
3.4.3. Methodology
3.4.4. Results
3.4.5. Conclusions
3.5. Conclusions on Capital and Offshore Wealth
4: International Corporate Tax Avoidance
4.1. Empirical Findings on International Corporate Tax Avoidance
4.1.1. Overview
4.1.2. Data
4.1.3. Methodology
4.1.4. Results
4.1.5. United States
4.1.6. Europe
4.2. Estimates for the World, and Low- and Middle-income Countries in Particular
4.3. IMF’s Crivelli et al. (2016)
4.3.1. Overview
4.3.2. Data
4.3.3. Methodology
4.3.4. Results
4.3.5. Conclusions
4.4. UNCTAD (2015)
4.4.1. Overview
4.4.2. Data
4.4.3. Methodology
4.4.4. Results
4.4.5. Conclusions
4.5. OECD (2015b)
4.5.1. Overview
4.5.2. Data
4.5.3. Methodology
4.5.4. Results
4.5.5. Conclusions
4.6. Profit Shifting of US Multinationals Worldwide (Clausing, 2016)
4.6.1. Overview
4.6.2. Data
4.6.3. Methodology
4.6.4. Results
4.6.5. Conclusions
4.7. Misalignment of Profits and Economic Activity of US Multinationals Worldwide (Cobham & Janský, 2019)
4.7.1. Overview
4.7.2. Data
4.7.3. Methodology
4.7.4. Results
4.7.5. Conclusions
4.8. Corporate Income Tax Efficiency Estimates (IMF (2014), EPRS (2015))
4.8.1. Overview
4.8.2. Data
4.8.3. Methodology
IMF (2014)
EPRS (2015)
4.8.4. Results
4.8.5. Conclusions
4.9. Tørsløv, Wier, & Zucman (2018)
4.9.1. Overview
4.9.2. Data
4.9.3. Methodology
4.9.4. Results
4.9.5. Conclusions
4.10. Conclusions on International Corporate Tax Avoidance
PART 3: PROPOSALS FOR IFF MONITORING
5: Beyond Scale: Risk- and Policy-based Indicators
5.1. Policy Measures
5.2. Financial Secrecy Literature
5.3. Bilateral Financial Secrecy Index
5.4. IFF vulnerability measures
5.5. Conclusions
6: New Proposals for IFF Indicators in the Sustainable Development Goals
6.1. Profit Shifting: SDG 16.4.1a
6.1.1. Overview
6.1.2. Data
6.1.3. Methodology
6.1.4. Conclusions
6.2. Undeclared Offshore Assets: SDG 16.4.1b
6.2.1. Overview
6.2.2. Data
6.2.3. Methodology
6.2.4. Results
6.2.5. Conclusions
6.3. Combining the Two Components
7: Conclusion: Estimating illicit financial flows
7.1. Definition of Illicit Financial Flows
7.2. Estimates of IFF
7.2.1. Trade estimates
7.2.2. Capital and offshore wealth
7.2.3. International corporate tax avoidance
7.3. IFF Indicators
7.3.1. Non-scale IFF indicators
7.3.2. SDG proposals
7.4. Conclusions
References
Index
